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NTT and Qualcomm use 5G to bring AI to edge
- October 4, 2023
- Steve Rogerson
Japanese IT infrastructure and services company NTT is partnering Qualcomm to facilitate private 5G adoption, which is critical to powering AI at the edge.
As part of a multi-year engagement, NTT and Qualcomm will prioritise the development of 5G- enabled devices to accelerate innovation with global enterprise customers, a critical catalyst in driving widespread enterprise adoption of private 5G, a market IDC estimates will exceed $8bn by 2026.
Qualcomm’s application specific semiconductors and 5G chipsets combined with NTT’s private 5G should strengthen the 5G ecosystem, advance AI processing capabilities at the edge and spur innovation across industries.
With enterprises accelerating digitisation efforts, more connectivity and even more devices are needed. NTT and Qualcomm will use their combined expertise to meet the need for 5G-enabled devices that support use cases, such as push-to-talk devices, augmented reality headsets, computer vision cameras and sensors at the edge across the manufacturing, automotive, logistics and other industries.
“This collaboration is truly an exciting one because we are answering the demand we’re hearing from our clients,” said Shahid Ahmed, executive vice president at NTT. “Together with Qualcomm, we will strengthen the 5G ecosystem delivering the devices our customers require in a simple and cost-effective way, empowering them as they continue along their digital transformation journey. By working with Qualcomm, we will further accelerate demand for private 5G across global industries.”
Mark Bidinger from Schneider Electric added: “The proliferation of 5G-enabled devices is a critical component of shaping a more digital and sustainable future. It forms the backbone of many tech advancements that can improve efficiency and sustainability through efficient resource management, energy conservation, and are pivotal for innovation across various industries. NTT’s collaboration with Qualcomm represents a significant step forward in advancing private 5G adoption and meeting the unique demands of the internet of things and machine learning.”
For AI to scale and make an impact on enterprise operations and organisations’ bottom line, AI processing needs to happen in a hybrid form, both in the cloud and at the edge of the network. The silicon that Qualcomm develops includes built-in AI and machine-learning models, making it well-positioned for growing AI capabilities at the edge. Qualcomm’s experience with scaling AI technology allows the company to touch a wide range of devices and applications including smartphones, laptops, sensors, automotive and networking.
“Qualcomm’s 5G chipsets are prepared for the widespread adoption of AI applications at the edge and, together with NTT, we’ll enhance innovative change across the 5G device ecosystem,” said Jeffery Torrance, senior vice president at Qualcomm. “NTT is the voice of the customer and, combined with Qualcomm’s semiconductor expertise, we can enable OEMs to build the devices that will benefit a wide range of use cases and customers.”
Qualcomm (www.qualcomm.com) and NTT will work together to deliver 5G-ready devices with Qualcomm’s 5G chipsets with AI models built in to enhance AI at the edge through various applications, such as image recognition, with capabilities ranging from counting items and identifying object characteristics to verifying workers wearing safety masks or hardhats. Deploying AI applications through NTT’s edge-as-a-service will assist enterprises with workplace safety, optimisation and security.
As part of NTT’s end-to-end edge-as-a-service offering, NTT (services.global.ntt) is now offering managed services for device-as-a-service to make it easy for users to access, upgrade and recycle 5G and edge devices and simplify device lifecycle management as well as reduce IT maintenance and costs.
The per-user, per-month fee model means enterprises no longer need to make large capital investments upfront, but rather consume on a more comfortable monthly fee basis, making it easier for them to deploy edge devices at scale.